CN110555067A - method for collecting, processing and integrally managing assembly quality data - Google Patents
method for collecting, processing and integrally managing assembly quality data Download PDFInfo
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Abstract
the invention discloses a method for collecting, processing and integrally managing assembly quality data. The method comprises the steps of collecting and managing assembly data, and specifically comprises the following steps: 1) collecting information of personnel and materials by a radio frequency identification technology and a bar code identification mode; 2) collecting material and environment information through a laser tracker, a laser radar, a three-dimensional coordinate measuring instrument, indoor iGPS measurement and a digital measuring instrument device for articulated arm measurement; 3) converting and exporting method information from digital application systems of CAD, DELMIA, 3DVIA Composer, ERP and MES; 4) performing data access on the assembly quality data source; 5) preprocessing data, namely extracting data, converting data and loading data; 6) constructing a temporary data storage mode and storing the data processed for the first time in a temporary transition area; 7) and returning to the step 5) until target data is obtained. The invention is suitable for data management with high data dimension, large information amount and complex structure, and the analysis method is more scientific and reasonable.
Description
Technical Field
The invention relates to the technical field of industrial data management, in particular to a method for collecting, processing and integrally managing assembly quality data.
background
the assembly process generates a large amount of process information and data that provides detailed records of the assembly of the aircraft and its performance, relating to various aspects of personnel, equipment, parts, inspection, quality, processing, manufacturing and management. Because the data types are various, the correlation is obvious, the sources are various, the traditional data analysis depends on the experience of experts, and the following defects exist: 1. the engineering data type is complicated, the relation is loose, abundant data resources are not effectively integrated, a unified and effective analysis and processing means 2 is lacked, the analysis process seriously depends on subjective experience, the efficiency is low, the analysis flow is not standard, the theoretical basis is insufficient, and the analysis result is difficult to reproduce.
disclosure of Invention
the invention aims to provide a method for acquiring, processing and integrally managing assembly quality data, so that the acquisition and integrated management of the assembly quality data can be accurately and completely acquired in real time, and subsequent quality analysis and control can be carried out.
The technical solution for realizing the purpose of the invention is as follows: a method for collecting, processing and integrally managing assembly quality data comprises the steps of collecting and managing the assembly data, and specifically comprises the following steps:
Step 1: collecting information of personnel and materials by a radio frequency identification technology and a bar code identification mode;
Step 2: collecting material and environment information through a laser tracker, a laser radar, a three-dimensional coordinate measuring instrument, indoor iGPS measurement and a digital measuring instrument device for articulated arm measurement;
and step 3: converting and exporting method information from digital application systems of CAD, DELMIA, 3DVIA Composer, ERP and MES;
and 4, step 4: performing data access on the assembly quality data source;
And 5: preprocessing data, namely extracting data, converting data and loading data;
step 6: constructing a temporary data storage mode and storing the data processed for the first time in a temporary transition area;
And 7: and (5) repeating the step (5) to the step (7) until target data are obtained.
Further, the data extraction in step 5 is specifically as follows:
the data extraction is a data input link, namely extracting data from a plurality of heterogeneous data sources including external application systems and databases to a uniform data storage area;
The ETL data extraction is divided into full extraction and incremental extraction according to different extraction time, the full ETL extraction is that all data of all charts in the source data are extracted when a data warehouse is initialized, and the incremental ETL extraction is that only data which are changed and newly added after the last extraction in the incremental maintenance of the data warehouse are extracted;
the maintenance and updating work of the data warehouse is realized by adopting an incremental ETL extraction method through triggers, and 3 triggers are installed for creating, changing and deleting the extracted data; when the data changes, the trigger starts to work and records the data in the temporary transition table, and incremental data is extracted from the temporary transition table.
further, the data conversion in step 5 is specifically as follows: the data conversion is to perform data merging and summarizing, format unification, file filtering, and key data reconstruction and positioning on the extracted data.
Further, the data loading in step 5 is specifically as follows:
The data loading is a data output link, namely, the extracted, converted and cleaned clean data is temporarily stored and loaded into a target database from unified data according to the definition of a physical model and a logical model, and meanwhile, manual intervention is allowed, and the functions of system log, error alarm, data backup and recovery are provided.
Compared with the prior art, the invention has the following remarkable advantages: (1) data are acquired in real time from the aspects of equipment, environment, materials and the like, and are stored, cleaned and analyzed by using a big data technology, so that empirical data analysis is avoided, and the analysis method is more scientific and reasonable; (2) the method is suitable for the characteristics of high data dimensionality, large information amount and complex structure, and can acquire the collection and integrated management of the assembly quality data accurately and completely in real time and perform subsequent quality analysis and control.
Drawings
Fig. 1 is a general scheme diagram of the assembly quality data collection, processing and integrated management method of the present invention.
FIG. 2 is a diagram of a data mapping model architecture in the method of the present invention.
FIG. 3 is a diagram of the data extraction, transformation and loading relationships of the present invention.
Detailed Description
The invention relates to a method for collecting, processing and integrally managing assembly quality data, which comprises the following steps of collecting and managing the assembly data:
step 1: collecting information of personnel and materials by a radio frequency identification technology and a bar code identification mode;
step 2: collecting material and environment information through a laser tracker, a laser radar, a three-dimensional coordinate measuring instrument, indoor iGPS measurement and a digital measuring instrument device for articulated arm measurement;
And step 3: converting and exporting method information from digital application systems of CAD, DELMIA, 3DVIA Composer, ERP and MES;
And 4, step 4: performing data access on the assembly quality data source;
And 5: preprocessing data, namely extracting data, converting data and loading data;
Step 6: constructing a temporary data storage mode and storing the data processed for the first time in a temporary transition area;
and 7: and (5) repeating the step (5) to the step (7) until target data are obtained.
Further, the data extraction in step 5 is specifically as follows:
The data extraction is a data input link, namely extracting data from a plurality of heterogeneous data sources including external application systems and databases to a uniform data storage area;
The ETL data extraction is divided into full extraction and incremental extraction according to different extraction time, the full ETL extraction is that all data of all charts in the source data are extracted when a data warehouse is initialized, and the incremental ETL extraction is that only data which are changed and newly added after the last extraction in the incremental maintenance of the data warehouse are extracted;
the maintenance and updating work of the data warehouse is realized by adopting an incremental ETL extraction method through triggers, and 3 triggers are installed for creating, changing and deleting the extracted data; when the data changes, the trigger starts to work and records the data in the temporary transition table, and incremental data is extracted from the temporary transition table.
Further, the data conversion in step 5 is specifically as follows: the data conversion is to perform data merging and summarizing, format unification, file filtering, and key data reconstruction and positioning on the extracted data.
Further, the data loading in step 5 is specifically as follows:
The data loading is a data output link, namely, the extracted, converted and cleaned clean data is temporarily stored and loaded into a target database from unified data according to the definition of a physical model and a logical model, and meanwhile, manual intervention is allowed, and the functions of system log, error alarm, data backup and recovery are provided.
Example 1
the assembly is the most important link in the industrial manufacturing process, and the quality level of the assembly is directly influenced by timely and effective acquisition and efficient reasonable integration of quality data. The invention is used for acquiring and integrally managing the assembly quality data in real time, accurately and completely and carrying out subsequent quality analysis and control.
1. Content and method of assembly data collection
(1) data acquisition content:
a large amount of dynamic assembly data streams can be generated on the assembly workshop site along with the progress of an assembly process, and people, equipment, materials, methods and environments which are called 4M1E for short are provided according to a classical quality data classification method "
The specific contents are as follows:
1) person (Man): the system comprises designers, technologists, assemblers, detection personnel and the like, and the data of education degree, professional skill level, physical health condition, psychological diathesis condition and the like of the personnel.
2) Device (Machine): the service life, operation condition, maintenance condition, failure frequency and other data of the equipment can be used as the assembly data content of statistical analysis.
3) Materials (materials): the manufacturing precision, material, overall dimension and other data of the material are all used as basic data content of assembly.
4) process (Method): the process method comprises data such as an aircraft assembly process plan and a detection process plan.
5) Environment (Environment) environmental factors at the assembly site, such as humidity, temperature, lighting, air pressure, noise, vibration, etc., can be used to provide data on personnel, equipment, materials, etc.
(2) the data acquisition method comprises the following steps:
The digital acquisition method mainly comprises data acquisition modes such as Radio Frequency Identification (FRID) technology, bar code Identification technology and the like. And various advanced assembly measurement devices such as laser trackers, lidar, three-dimensional coordinate measuring machines, indoor iGPS measurements, articulated arm measurements, and the like. The method also comprises the conversion and import of the data of each digital application system, such as data information generated by application systems of CAD, DELMIA, 3DVIAComposer, ERP, MES and the like.
2. Quality data integration management
Data integration is a data management technology aiming at integrating data of various systems to realize data sharing among various information systems and providing convenient services for fully and effectively utilizing system resources. The digital assembly quality data has the following characteristics due to various acquisition and generation modes, complex manufacturing process and the like: high data dimension, multi-source data, large information quantity, heterogeneous data, poor data quality and the like. Aiming at the current situations that the data lack unified specification, are not standardized, can not well realize data sharing, fully utilize the data to improve the assembly quality and the like, the technology carries out integrated management on the data, establishes a data integrated management system and realizes multi-source heterogeneous data integration.
(1) overall scheme design
The essence of quality multi-source heterogeneous data integration is to scientifically and reasonably and organically integrate data of various sources, various formats and various properties through a certain data management means in physical and logical aspects, and provide basic data conditions for scientific analysis and other work. The scheme firstly carries out data access on an assembly quality data source and designs a universal access interface. Meanwhile, a data extraction, transformation and loading (ETL) technology is adopted to preprocess data, namely operations such as data transformation, data extraction and data loading, by establishing a mapping model corresponding to metadata and target data. Because the ideal target data is difficult to obtain by simply carrying out conventional one-time ETL (extract transform and load) on the characteristics of high dimensional quantity and large data, the first-time ETL data is stored in a temporary transition region by adopting a temporary data storage mode, and then the target data can be easily obtained by carrying out one-time ETL on the data, so that the ideal multi-source heterogeneous quality data integration management is realized. The overall design is shown in fig. 1.
(2) Data mapping model
The quality data mapping means that a logical relation corresponding to a target database is established by source data collected through a data access interface, and the data mapping is not a simple corresponding relation and is a process of finding out and structuring internal relation between the two data through a certain algorithm. And (3) establishing a quality data mapping model, wherein the mapping model is divided into four levels, namely a field level, a table level, a file level and a database level, and is shown in figure 2.
(3) ETL scheme
Data extraction, transformation and loading (ETL) is proposed with a data warehouse, which is also an important method for data integration. The ETL technology mainly performs data preparation activities such as extraction, conversion, cleaning, and loading on data of various information systems, and provides required data preparation for an intelligent system, so ETL is a key link of data integration, as shown in fig. 3.
1) Data extraction
data extraction is a data input link and mainly aims to solve the data multi-source heterogeneous problem, namely data are extracted from a plurality of heterogeneous data sources such as external application systems and databases to a unified data storage area. The extraction of the ETL data can be divided into full extraction and incremental extraction according to different extraction time, the full ETL extraction is that all data such as charts in the source data are extracted when the data warehouse is initialized, and the incremental ETL extraction is that only the data changed and newly added after the last extraction is extracted in the incremental maintenance of the data warehouse. The ETL design realizes the maintenance and updating work of a data warehouse by adopting an incremental ETL extraction method through a trigger, 3 triggers are installed for creating, changing and deleting the extracted data, when the trigger starts working under the condition of change such as data change and the like, the data are recorded in a temporary transition table, and the incremental data are extracted from the temporary transition table.
2) Data conversion
The data conversion refers to the operations of data merging and summarizing, format unification, file filtering, reconstruction and positioning of key data and the like on the extracted data, and the data conversion and processing are particularly important because the data formats are not unified, the data are incomplete and the data reading failure is easily caused.
3) Data loading
Data loading is the output link of data, namely, the process of temporarily storing and loading the extracted, converted and cleaned clean data into a target database from unified data according to the definition of a physical and logical model, and simultaneously allowing manual intervention and providing the functions of system logging, error alarm, data backup and recovery, wherein the process is the final step of the ETL.
Claims (4)
1. a method for collecting, processing and integrated management of assembly quality data is characterized by comprising the following steps of collecting and managing the assembly data:
Step 1: collecting information of personnel and materials by a radio frequency identification technology and a bar code identification mode;
Step 2: collecting material and environment information through a laser tracker, a laser radar, a three-dimensional coordinate measuring instrument, indoor iGPS measurement and a digital measuring instrument device for articulated arm measurement;
And step 3: converting and exporting method information from digital application systems of CAD, DELMIA, 3DVIA Composer, ERP and MES;
and 4, step 4: performing data access on the assembly quality data source;
And 5: preprocessing data, namely extracting data, converting data and loading data;
Step 6: constructing a temporary data storage mode and storing the data processed for the first time in a temporary transition area;
and 7: and (5) repeating the step (5) to the step (7) until target data are obtained.
2. The assembly quality data acquisition, processing and integrated management method according to claim 1, wherein the data extraction in step 5 is as follows:
the data extraction is a data input link, namely extracting data from a plurality of heterogeneous data sources including external application systems and databases to a uniform data storage area;
the ETL data extraction is divided into full extraction and incremental extraction according to different extraction time, the full ETL extraction is that all data of all charts in the source data are extracted when a data warehouse is initialized, and the incremental ETL extraction is that only data which are changed and newly added after the last extraction in the incremental maintenance of the data warehouse are extracted;
the maintenance and updating work of the data warehouse is realized by adopting an incremental ETL extraction method through triggers, and 3 triggers are installed for creating, changing and deleting the extracted data; when the data changes, the trigger starts to work and records the data in the temporary transition table, and incremental data is extracted from the temporary transition table.
3. The assembly quality data acquisition, processing and integrated management method according to claim 1, wherein the data conversion in step 5 is as follows: the data conversion is to perform data merging and summarizing, format unification, file filtering, and key data reconstruction and positioning on the extracted data.
4. The assembly quality data acquisition, processing and integrated management method according to claim 1, wherein the data loading in step 5 is as follows:
The data loading is a data output link, namely, the extracted, converted and cleaned clean data is temporarily stored and loaded into a target database from unified data according to the definition of a physical model and a logical model, and meanwhile, manual intervention is allowed, and the functions of system log, error alarm, data backup and recovery are provided.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111626548A (en) * | 2020-04-07 | 2020-09-04 | 青岛奥利普自动化控制系统有限公司 | Quality management method and equipment based on MES system |
| CN111986042A (en) * | 2020-08-24 | 2020-11-24 | 绵阳上策网络科技有限公司 | Agricultural big data service system constructed based on internet technology |
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2018
- 2018-03-30 CN CN201810289808.4A patent/CN110555067A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111626548A (en) * | 2020-04-07 | 2020-09-04 | 青岛奥利普自动化控制系统有限公司 | Quality management method and equipment based on MES system |
| CN111986042A (en) * | 2020-08-24 | 2020-11-24 | 绵阳上策网络科技有限公司 | Agricultural big data service system constructed based on internet technology |
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